The central obstacle the researchers faced was a confound familiar to anyone who studies reward in animals. When a mouse drinks water or eats food, its cerebellum is obviously active, but that activity could simply reflect the exquisite motor coordination of jaw, tongue, and forelimb movements rather than any representation of reward value. Disentangling the two requires an experimental design in which reward arrives without any consummatory behavior. The team’s solution was elegant: they trained head-fixed mice to push a robotic manipulandum, and each successful push delivered a delayed dose of dopamine directly into the brain, either through optogenetic activation of dopamine neurons in the ventral tegmental area or through electrical stimulation of the medial forebrain bundle, a classic self-stimulation pathway known to powerfully reinforce behavior. In this push-for-dopamine task, reward is stripped of its natural consummatory movements, leaving any cerebellar reward signals nowhere to hide.

While mice performed the task, the researchers used two-photon calcium imaging to watch two fundamentally different input streams of the cerebellar cortex simultaneously. The first stream consisted of cerebellar granule cells, the tiny, extraordinarily numerous neurons that receive mossy fiber inputs and form the parallel fiber system that broadcasts information across the cerebellum. The second stream was the climbing fibers, the powerful axons originating in the inferior olive that wrap around Purkinje cells and have long been associated with teaching signals in motor learning. By imaging granule cells with GCaMP indicators and climbing fiber terminals with the red calcium sensor RCaMP2, the team could record both channels of cerebellar input during the same behavioral sessions, capturing how each population responded as mice anticipated, earned, and consumed dopamine rewards.

The granule cell results were striking. Many individual granule cells encoded upcoming dopamine rewards predictively, ramping up sustained activity during the one-second delay between the completed push and reward delivery, and then terminating that activity abruptly the moment the reward arrived. This was not a brief burst locked to the action; it was a slowly building expectation signal that stretched or compressed to match the timing of the reward itself. When the researchers trained mice with two-second delays instead of one, the granule cell activations stretched correspondingly longer, and single-trial analyses confirmed that individual neural responses genuinely temporally scaled rather than simply broadening through trial averaging. When rewards were occasionally omitted, the anticipatory ramp persisted and failed to quench, exactly what one would expect from a signal tracking expected reward rather than the physical act of reaching.

Crucially, the researchers ran a battery of controls to rule out the possibility that these ramping signals were secretly encoding movement. DeepLabCut-based tracking of jaw, forepaw, nose, and hindpaw kinematics showed that the neural expectation dynamics diverged sharply from movement profiles: in some analyses, neural expectation peaked precisely when physical movement was minimal, and variance-partitioning models demonstrated that for most reward-anticipating granule cells, reward regressors explained neural activity far better than concurrent body kinematics did. The team even showed that anticipatory ramping appeared in a purely passive paradigm, in which an auditory cue predicted dopamine delivery with no instrumental action required at all. The expectation timer, in other words, does not depend on prior motor execution.

Perhaps most surprising was how the dopamine signal compared with a natural reward. In mice trained on both the push-for-dopamine task and an analogous push-for-water task, the strength of granule cell reward encoding for artificial dopamine stimulation matched or exceeded the encoding for water. Individual granule cells frequently generalized across reward types, and separate populations of cells generalized across delay durations, suggesting a common internal representation of anticipated reward value and timing that transcends the specific sensory identity of the reinforcer. Prior water training was not necessary for dopamine reward prediction signals to emerge, and animals that failed to reduce their orofacial movements upon switching from water to dopamine did not disproportionately drive the population-level anticipation effect, further dissociating reward expectation from consummatory habit.

The climbing fibers told a different and complementary story. Whereas granule cells predicted rewards, the majority of climbing fibers spiked just after dopamine delivery, firing robustly within a short latency of reward arrival on the very first day of training in naive animals. Many of the same climbing fibers also responded after water rewards, and responses to dopamine were typically stronger than responses to water in cells responsive to both. The researchers propose that this post-reward climbing fiber activity functions as an instructive, teaching-like signal, the cerebellar analogue of the dopamine system’s own reward delivery response. In classical cerebellar theory, climbing fiber activity serves as an error signal that drives synaptic plasticity at parallel fiber-Purkinje cell synapses; the new data suggest that reward arrival itself can constitute such a signal, allowing the cerebellum to strengthen the associations between actions, temporal expectations, and rewarding outcomes.

Both codes proved causally important, not merely correlational. When the researchers chronically inhibited granule cell activity with the optogenetic chloride pump stGtACR1 throughout the delay period and across multiple training days, mice learning the push-for-dopamine task were significantly impaired: they improved less in successful pushes per minute and in the percentage of completed reaches compared with normally trained controls. Importantly, the deficit persisted into a subsequent laser-off washout session, confirming that chronic granule cell inhibition disrupted the actual acquisition of the task rather than merely producing an acute motor impairment during stimulation. On the instructive side, the team asked whether climbing fiber activation alone could serve as a reward. In a remarkable demonstration, naive mice learned to push at moderate rates for delayed optogenetic activation of their own climbing fibers, receiving no dopamine and no natural reward whatsoever. Climbing fiber self-stimulation was less powerful than true dopamine or water rewards, falling into a rough motivational hierarchy of climbing fiber below ventral tegmental area stimulation below medial forebrain bundle and water, yet it was sufficient to support operant learning, accompanied by the same predictive granule cell ramping observed for genuine rewards.

Together, these results sketch a cerebellum that is deeply embedded in the machinery of motivation. Granule cells provide a predictive code, a running estimate of when and whether reward will arrive that scales with delay duration and reward type, while climbing fibers deliver an instructive code that marks rewarding outcomes and can itself reinforce actions. Because the cerebellum maintains well-characterized reciprocal connections with the basal ganglia, the thalamus, and reward-related cortical regions, these signals are positioned to interact with midbrain dopamine circuitry rather than operate in parallel to it. The authors suggest that cerebellar reward encoding may contribute to how animals learn the timing and value of their actions, integrating the prediction of future reward with the motor programs needed to obtain it.

The broader implications are considerable. Conditions ranging from Parkinson’s disease and addiction to autism and ataxia have all been linked, in various ways, to disrupted reward processing or cerebellar dysfunction, and several psychiatric and neurological disorders increasingly show cerebellar signatures in neuroimaging studies of motivation and cognition. If cerebellar granule cells and climbing fibers genuinely encode and instruct reward, then models of reinforcement learning that treat dopamine as the sole teaching signal may need revision, and the cerebellum may emerge as a target for therapeutic strategies aimed at restoring motivated behavior. At minimum, the study delivers a vivid demonstration that a structure long confined to the motor periphery of neuroscience is, in fact, keeping its own account of the brain’s most valuable currency, and using that account to help drive the actions that earn it.

Subject of Research: Cerebellar neural encoding of dopamine reward prediction and reinforcement in motivated behavior

Article Title: Predictive and instructive cerebellar encoding of dopamine reward drives motivated behavior

Article References: Predictive and instructive cerebellar encoding of dopamine reward drives motivated behavior. (n.d.). https://doi.org/10.1038/s41593-026-02449-z

Image Credits: AI Generated

DOI: 10.1038/s41593-026-02449-z

Keywords: cerebellum, dopamine, reward prediction, granule cells, climbing fibers, motivated behavior, two-photon imaging, optogenetics, intracranial self-stimulation, reinforcement learning, neural circuits, Nature Neuroscience